title: Accurate localization of in-body medical implants based on spatial sparsity.
abstract: Wearable and implantable wireless communication devices have in recent years gained increasing attention for medical diagnostics and therapeutics. In particular, wireless capsule endoscopy has become a popular method to visualize and diagnose the human gastrointestinal tract. Estimating the exact position of the capsule when each image is taken is a very critical issue in capsule endoscopy. Several approaches have been developed by researchers to estimate the capsule location. However, some unique challenges exist for in-body localization, such as the severe multipath issue caused by the boundaries of different organs, inconsistency of signal propagation velocity and path loss parameters inside the human body, and the regulatory restrictions on using high-bandwidth or high-power signals. In this paper, we propose a novel localization method based on spatial sparsity. We directly estimate the location of the capsule without going through the usual intermediate stage of first estimating time-of-arrival or received-signal strength, and then a second stage of estimating the location. We demonstrate the accuracy of the proposed method through extensive Monte Carlo simulations for radio frequency emission signals within the required power and bandwidth range. The results show that the proposed method is effective and accurate, even in massive multipath conditions.
authors.forename: Mohammad
authors.initials: M
authors.lastname: Pourhomayoun
authors.forename: Zhanpeng
authors.initials: Z
authors.lastname: Jin
authors.forename: Mark L
authors.initials: ML
authors.lastname: Fowler
mesh_terms: D000465:Algorithms; D053704:Capsule Endoscopy / Q000295:instrumentation* / Q000379:methods; D003195:Computer Communication Networks / Q000295:instrumentation; D003198:Computer Simulation; D006801:Humans; D018670:Monitoring, Ambulatory / Q000295:instrumentation* / Q000379:methods; D012815:Signal Processing, Computer-Assisted; D059629:Signal-To-Noise Ratio